Social and housing indicators of dengue and chikungunya in Indian adults aged 45 and above: Analysis of a nationally representative survey (2017-18)

Background Dengue and chikungunya (CHIKV) are the two major vector-borne diseases of serious public health concern in India. Studies on socioeconomic and housing determinants of dengue and CHIKV at a pan-India level are lacking. Here, we took advantage of the recently carried out Longitudinal Ageing Study in India (LASI) carried out across all the states and Union Territories of India to study the social indicators of dengue and CHIKV in India. Methods LASI-1 (2017-2018) data on the self-reported period prevalence of dengue and CHIKV from 70,932 respondents aged ≥45 years were used for this analysis. The state-wise distribution of dengue and CHIKV was mapped. Prevalence was estimated for each study variable, and the difference was compared using the χ2 test. The adjusted odds ratios (AOR) of the socioeconomic and housing variables for dengue and CHIKV were estimated using the multiple logistic regression model. Results Urban residence is the major socio-economic indicator of dengue and CHIKV (dengue AOR: 1.57, 95% CI: 1.18-2.11; CHIKV AOR: 1.84, 95% CI: 1.36-2.49). The other notable indicator is wealth; rich respondents have higher odds of dengue and CHIKV. Adults older than 54 years and those with high school education and above are associated with a lower likelihood of dengue and CHIKV. In addition, CHIKV is associated with scheduled and forward castes, households with improper toilet facilities, open defecation, and kutcha house type. Conclusions Despite the limitation that the data is only from adults ≥ 45, this analysis provides important insights into the socioeconomic and housing variables associated with higher odds of dengue and CHIKV in India. Understanding these determinants may assist in the national planning of prevention and control strategies for dengue and CHIKV. Supplementary Information The online version contains supplementary material available at 10.1186/s13690-022-00868-5.

Our point-by-point comments to the reviewers' questions are addressed below

Reviewer#1:
The reviewer has the following comments: 1. Please fully follow one of the EQUATOR Network Reporting Guidelines for the reporting of this study (e.g., the STROBE network). Please write in the manuscript that you have followed such statement.
Thank you for your suggestion. This study has followed the STROBE guidelines, and we have mentioned it in statistical analysis under the methods section 2. Please fully follow the guidelines for the submission of this manuscript to the journal as some sections are missing or should not be reported.
Thank you for the suggestion.
Accordingly, we have made the following edits.
• Author summary has been removed • Limitation has been now moved to the discussion section (last paragraph) from the conclusion section • Pages are numbered • Figures-caption and legend have been included • Tables-size have been adjusted to fit the journal requirement Reviewer #2: This study used data from a nationally representative survey to examine the association between socioeconomic factors and self-reported dengue and chikungunya prevalence. The authors found that urban residency, education level, wealth status, toilet or house type are significant factors for both diseases. Overall, the manuscript is well written, methods are described in adequate detail, statistical methods are sound, and the discussion has covered most aspect of the results in the context of the literature and dengue/chikungunya situation in other countries. Nevertheless, the manuscript can be further improved with the following points: Due to the self-report nature of the study, only considering individuals treated by health professionals may bias the results to show higher odds for those who are wealthy and highly educated. This is discussed briefly in the discussion. However, I recommend a sensitivity analysis on those who self-reported having dengue or chikungunya in the past two years. The sensitivity analysis will verify whether the positive associations for the wealthiest/highly educated/forward castes still hold.
Thank you for your suggestion. Dengue and CHIKV infections are often mild and mostly go undiagnosed or misdiagnosed. Hence, we have only considered those who had self-reported dengue/CHIKV infection and were also treated for these two diseases. The self-reported dengue cases were 674; of those, 607 (91%) got treated by a health professional, CHIKV cases were 1427, and 1358 (95%) were treated by a health professional. Most (>90%) of the self-reported cases got treated, which implies that they are indeed cases of dengue/CHIKV. A separate analysis for the actual self-reported cases with predictors and what the authors have considered (who had self-reported dengue/CHIKV infection and also got treated for these two diseases) and the predictors were performed. There was hardly any difference in the analyses except for slight variations in values. The positive associations for the wealthiest/highly educated/forward castes did not change after the sensitivity analysis.
Throughout the manuscript, avoid stating that certain factors "increase" the odds of dengue/chikungunya since the analysis are only meant for identifying "association" between factors and outcome, but not identifying causality relationship Thank you for this important suggestion. We have modified accordingly. Furthermore, we have replaced determinants in the title with indicators.
"Social and housing determinants indicators of dengue and chikungunya in Indian adults aged 45 and above: Analysis of a nationally representative survey (2017-18)"

Why not mentioning urban residency and age as important factors in the abstract?
We have added a statement of these two variables in the abstract.

Done
Line 102, should mention the species are mosquito species

Methods should briefly explain the sampling design. Did they sample within state/urban-rural setting? Is it nationally representative?
Again, we appreciate this important suggestion and the paragraph below is included in the methods section.
"The LASI wave 1 is a nationally representative study of all states and Union Territories (UT)except Sikkim. The survey gathered vital information on health, infectious diseases, socioeconomic determinants, and consequences of population ageing from 72,252 individuals. A multistage clustering sampling design was adopted to obtain the data from the non-institutional residents aged ≥45 years and their spouses (regardless of age). In the first stage of the sampling process, primary sampling units, i.e., sub-districts (Tehsils/Talukas), were selected in each state/UT. During the second stage, villages (rural areas) and wards (urban areas) were selected from all the primary sampling units and in the third stage, households and individuals were selected. The sampling procedure was extended by one more step in the urban areas where a census enumeration block was chosen before selecting households" Line 170, why did you exclude the untreated respondents from the analysis, since you can consider them as not having the two diseases but still kept them in the model?
The sample size earlier was 70,865, and now it is 70,932 after including the untreated respondents. The analysis was repeated again with 70,932 respondents.

Line 177 should consider separating toilet-type into three groups: flushed types, pit/latrine/twin pit/composting toilet, and open defecation.
As suggested, the toilet-type was coded into three types: flushed types, pit/latrine/twin pit/composting toilet, and open defecation, and we have re-run the analysis. Now, we find pit latrine/twin pit/composting toilet and open defecation to be associated with CHIKV.

Line 207, accurate [statistical] estimates
Done Line 207-209 should be introduced when you described the data and variables before statistical methods.
Thank you. The lines have been moved to the heading "data and participants"

Line 210, any patterns for those with missing values?
We have checked and have not observed any patterns for the missing value. The missing values are less than 2%.

Done
Line 215, which version of ArcGIS is used? Reference is required.
We have used ArcGIS 10.4, and have added the reference link

Line 216, why using average? You can obtain the national prevalence as the mid-point instead
We have considered mid-points and natural breaks in the datasets while determining class intervals for spatial representation. We have changed the statement to remove ambiguity Line 233, are the prevalence for dengue or chikungunya?
We have edited the statement

Conclusion should provide policy implications of the results
Briefly, we have written the policy implications in the conclusions.